Patents by Inventor Yufan Guo
Yufan Guo has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240127777Abstract: The present application relates to the technical field of computers, and discloses a method and apparatus for generating a music file, and an electronic device and a storage medium. The method for generating a music file comprises: obtaining a first image; performing feature extraction on the first image to obtain a salient feature of the first image; mapping the salient feature to a musical instrument digital interface (MIDI) information coordinate system on the basis of the position of the salient feature in the first image, so as to determine MIDI information corresponding to the salient feature, the MIDI information coordinate system being used for indicating a correspondence between MIDI information and time; and generating a music file on the basis of the correspondence between the MIDI information and the time.Type: ApplicationFiled: December 19, 2023Publication date: April 18, 2024Inventors: Yufan XUE, Guanjun GUO, Xin YUAN, Yuezhao CHEN, Hao HUANG, Na LI, Xubin ZHOU
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Patent number: 11935636Abstract: Methods and systems of summarizing medical data. One system includes an electronic processor configured to analyze medical data to extract a medical concept and a plurality of additional attributes of the medical concept and store the medical concept and the plurality of additional attributes. The electronic processor is configured to generate a first medical summary associated with the patient, where the first medical summary is based on the stored medical concept and at least a first additional attribute included in the stored plurality of additional attributes. The electronic processor is configured to receive a user interaction with the first medical summary. The electronic processor is configured to generate a second medical summary associated with the patient based on the user interaction, the second medical summary is based on the stored medical concept and at least a second additional attribute included in the stored plurality of additional attributes.Type: GrantFiled: April 26, 2019Date of Patent: March 19, 2024Assignee: Merative US L.P.Inventors: Mark D. Bronkalla, Yufan Guo, Weber Marett
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Publication number: 20230334375Abstract: A system includes a memory having instructions therein and at least one processor in communication with the memory. The at least one processor is configured to execute the instructions to determine a global-level importance magnitude value for a global-level importance of an explainable feature of a machine learning base model based on a first prediction of the machine learning base model. The at least one processor is also configured to execute the instructions to determine a global-level importance direction label for the global-level importance of the explainable feature based on the first prediction. The at least one processor is also configured to execute the instructions to generate a communication for presentation to a user based on a second prediction of the machine learning base model, based on the global-level importance magnitude value, and based on the global-level importance direction label.Type: ApplicationFiled: June 28, 2023Publication date: October 19, 2023Inventors: Zhe Liu, Yufan Guo, Jalal Mahmud, Rama Kalyani T. Akkiraju
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Patent number: 11720819Abstract: A system includes a memory having instructions therein and at least one processor in communication with the memory. The at least one processor is configured to execute the instructions to determine a global-level importance magnitude value for a global-level importance of an explainable feature of a machine learning base model based on a first prediction of the machine learning base model. The at least one processor is also configured to execute the instructions to determine a global-level importance direction label for the global-level importance of the explainable feature based on the first prediction. The at least one processor is also configured to execute the instructions to generate a communication for presentation to a user based on a second prediction of the machine learning base model, based on the global-level importance magnitude value, and based on the global-level importance direction label.Type: GrantFiled: May 29, 2020Date of Patent: August 8, 2023Assignee: International Business Machines, IncorporatedInventors: Zhe Liu, Yufan Guo, Jalal Mahmud, Rama Kalyani T. Akkiraju
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Publication number: 20230095258Abstract: A mechanism is provided for implement a discrepancy detection mechanism for detecting discrepancies between clinical notes and administrative records. Clinical concepts are extracted from the clinical notes and the administrative records in a patient's electronic medical records (EMRs). The extracted clinical concepts are filtered based on semantic type information to identify concepts that reference diseases or syndromes while also removing negated instances. Utilizing the positive mentions of diseases in clinical notes, the positive mentions of diseases or syndromes in the clinical notes are compared against each positive entry in the administrative records. A discrepancy summary is then generated for diseases or syndromes that failed to translate correctly from clinical notes to the administrative records in the patient's EMRs.Type: ApplicationFiled: November 29, 2022Publication date: March 30, 2023Inventors: YUFAN GUO, David J. Beymer, Tyler Baldwin, Vandana Mukherjee, Tanveer F. Syeda-Mahmood
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Patent number: 11574713Abstract: A mechanism is provided for implement a discrepancy detection mechanism for detecting discrepancies between clinical notes and administrative records. Clinical concepts are extracted from the clinical notes and the administrative records in a patient's electronic medical records (EMRs). The extracted clinical concepts are filtered based on semantic type information to identify concepts that reference diseases or syndromes while also removing negated instances. Utilizing the positive mentions of diseases in clinical notes, the positive mentions of diseases or syndromes in the clinical notes are compared against each positive entry in the administrative records. A discrepancy summary is then generated for diseases or syndromes that failed to translate correctly from clinical notes to the administrative records in the patient's EMRs.Type: GrantFiled: July 17, 2019Date of Patent: February 7, 2023Assignee: International Business Machines CorporationInventors: Yufan Guo, David J. Beymer, Tyler Baldwin, Vandana Mukherjee, Tanveer F. Syeda-Mahmood
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Patent number: 11536125Abstract: The present invention discloses a method for proppant suspension and suspension parameter optimization based on bubble bridge effect, comprising: select a proppant and hydrophobically modify its surface to obtain a hydrophobically surface-modified proppant; prepare a bubbly fracturing base fluid; make the first optimization of the base fluids according to the average radius of the proppant and the average radius of the bubbles of the base fluids; optimally select the base fluids selected for the second time according to the interaction energy between the proppant particle and the bubble after the hydrophobically surface-modified proppant mixed with the base fluid; the basic parameters of the bubbly fracturing base fluid selected at the third time were used for the perfect selection for proppant suspension. The present invention establishes a procedure on experimental evaluation and parameter calculation optimization by suspending fracturing proppant with the bubble bridge effect on the hydrophobic surface.Type: GrantFiled: June 20, 2022Date of Patent: December 27, 2022Assignee: Chengdu University of TechnologyInventors: Bin Yang, Hao Zhang, Yufan Guo, Bo Yang, Yin Zhong, Yang Yang, Wenjing Ma, Yue Li
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Patent number: 11461376Abstract: Embodiments provide a computer implemented method of evaluating one or more IR systems, the method including: providing, by a processor, a pre-indexed knowledge-based document to a pre-trained sentence identification model; identifying, by the sentence identification model, a predetermined number of query-worthy sentences from the pre-indexed knowledge-based document, wherein the query-worthy sentences are ranked based on a prediction probability value of each query-worthy sentence; providing, by the sentence identification model, the query-worthy sentences to a pre-trained query generation model; generating, by the query generation model, a query for each query-worthy sentence; and evaluating, by the processor, the one or more IR systems using the generated queries, wherein one or more searches are performed via the one or more IR systems, and the one or more searches are performed in a set of knowledge-based documents including the pre-indexed knowledge-based document.Type: GrantFiled: July 10, 2019Date of Patent: October 4, 2022Assignee: International Business Machines CorporationInventors: Zhe Liu, Peifeng Yin, Jalal Mahmud, Rama Kalyani T. Akkiraju, Yufan Guo
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Publication number: 20220051462Abstract: A cross-modality neural network transform for semi-automatic medical image annotation is provided. In various embodiments, an input medical image is mapped to a first vector in a text vector space. The first vector corresponds to the features of the medical image. A set of predetermined vectors is searched for a closest one of the predetermined vectors to the first vector. From the closest one of the predetermined vectors, one or more keywords is determined describing the input medical image.Type: ApplicationFiled: October 28, 2021Publication date: February 17, 2022Inventors: Yufan Guo, Mehdi Moradi
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Patent number: 11195313Abstract: A cross-modality neural network transform for semi-automatic medical image annotation is provided. In various embodiments, an input medical image is mapped to a first vector in a text vector space. The first vector corresponds to the features of the medical image. A set of predetermined vectors is searched for a closest one of the predetermined vectors to the first vector. From the closest one of the predetermined vectors, one or more keywords is determined describing the input medical image.Type: GrantFiled: October 14, 2016Date of Patent: December 7, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Yufan Guo, Mehdi Moradi
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Publication number: 20210374601Abstract: A system includes a memory having instructions therein and at least one processor in communication with the memory. The at least one processor is configured to execute the instructions to determine a global-level importance magnitude value for a global-level importance of an explainable feature of a machine learning base model based on a first prediction of the machine learning base model. The at least one processor is also configured to execute the instructions to determine a global-level importance direction label for the global-level importance of the explainable feature based on the first prediction. The at least one processor is also configured to execute the instructions to generate a communication for presentation to a user based on a second prediction of the machine learning base model, based on the global-level importance magnitude value, and based on the global-level importance direction label.Type: ApplicationFiled: May 29, 2020Publication date: December 2, 2021Inventors: Zhe Liu, Yufan Guo, Jalal Mahmud, Rama Kalyani T. Akkiraju
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Patent number: 11132511Abstract: A system configured to predict fine-grained affective states. The system comprising a processor configured to execute instructions to create training data comprising content conveying emotions, and to create a trained model by performing an emotion vector space model training process using the training data to train a model using a feed forward neural network that converts discrete emotions into emotion vector representations. The system uses the trained model to predict fine-grained affective states for text conveying an emotion.Type: GrantFiled: February 5, 2019Date of Patent: September 28, 2021Assignee: International Business Machines CorporationInventors: Zhe Liu, Jalal Mahmud, Anbang Xu, Yufan Guo, Haibin Liu, Rama Kalyani T. Akkiraju
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Patent number: 11100293Abstract: Negation scope analysis for negation detection is provided. In various embodiments, a phrase is read from a report collection. The phrase is searched for at least one of a predetermined set of negation keywords. A dependency parse tree is generated of the phrase. The dependency parse tree is traversed starting with the at least one of the predetermined set of negation keywords. Based on the traversal, a plurality of words of the phrase are determined that are spanned by the at least one of the predetermined set of negation keywords.Type: GrantFiled: February 7, 2020Date of Patent: August 24, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventor: Yufan Guo
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Patent number: 11069432Abstract: Automatic detection of disease presence from combining disease-specific measurements with textual descriptions of disease and its severity in unstructured textual reports is provided. In various embodiments, a knowledge graph of clinical concepts is read. Based on the knowledge graph, a plurality of associations are determined between disease names, symptoms, anatomical abnormalities, and qualifiers. A corpus of clinical reports is read. Based on the plurality of associations, a plurality of portions indicative of a disease condition are located within the corpus of clinical reports. Within each of the plurality of portions, name/value pairs are detected corresponding to measurements indicative of the disease condition. The measurements indicative of the disease condition are extracted.Type: GrantFiled: October 17, 2016Date of Patent: July 20, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Yufan Guo, Tanveer Syeda-Mahmood
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Patent number: 11010564Abstract: A computer-implemented method for fine-grained affective states prediction. The computer-implemented method creates training data comprising content conveying emotions. The method creates a trained model by performing an emotion vector space model training process using the training data to train a model using a feed forward neural network that converts discrete emotions into emotion vector representations. The trained model can be used to predict fine-grained affective states for text conveying an emotion.Type: GrantFiled: July 10, 2019Date of Patent: May 18, 2021Assignee: International Business Machines CorporationInventors: Zhe Liu, Jalal Mahmud, Anbang Xu, Yufan Guo, Haibin Liu, Rama Kalyani T. Akkiraju
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Patent number: 10984024Abstract: A mechanism is provided that implements a cognitive data processing system for automatically processing ambiguously labeled data associated with a medical image. The cognitive data processing system receives an ambiguously labeled set of training data in which the ambiguously labeled set of training data comprises portions of data and associated labels, and wherein at least one portion of data in the ambiguously labeled set of training data has a plurality of different labels that together render the portion of data ambiguously labeled. The cognitive data processing system configures an implementation of a model that comprises a loss term, a maximizing term, and a sparsity term. The cognitive data processing system processes the ambiguously labeled set of training data based on the model to identifying a mapping that minimizes a loss function and thereby train the cognitive data processing system.Type: GrantFiled: November 13, 2018Date of Patent: April 20, 2021Assignee: International Business Machines CorporationInventors: Yu Cao, Yufan Guo, Tanveer F. Syeda-Mahmood
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Patent number: 10936628Abstract: A mechanism is provided that implements a cognitive data processing system for automatically processing ambiguously labeled data associated with a medical image. The cognitive data processing system receives an ambiguously labeled set of training data in which the ambiguously labeled set of training data comprises portions of data and associated labels, and wherein at least one portion of data in the ambiguously labeled set of training data has a plurality of different labels that together render the portion of data ambiguously labeled. The cognitive data processing system configures an implementation of a model that comprises a loss term, a maximizing term, and a sparsity term. The cognitive data processing system processes the ambiguously labeled set of training data based on the model to identifying a mapping that minimizes a loss function and thereby train the cognitive data processing system.Type: GrantFiled: May 30, 2018Date of Patent: March 2, 2021Assignee: International Business Machines CorporationInventors: Yu Cao, Yufan Guo, Tanveer F. Syeda-Mahmood
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Publication number: 20210020277Abstract: A mechanism is provided for implement a discrepancy detection mechanism for detecting discrepancies between clinical notes and administrative records. Clinical concepts are extracted from the clinical notes and the administrative records in a patient's electronic medical records (EMRs). The extracted clinical concepts are filtered based on semantic type information to identify concepts that reference diseases or syndromes while also removing negated instances. Utilizing the positive mentions of diseases in clinical notes, the positive mentions of diseases or syndromes in the clinical notes are compared against each positive entry in the administrative records. A discrepancy summary is then generated for diseases or syndromes that failed to translate correctly from clinical notes to the administrative records in the patient's EMRs.Type: ApplicationFiled: July 17, 2019Publication date: January 21, 2021Inventors: Yufan Guo, David J. Beymer, Tyler Baldwin, Vandana Mukherjee, Tanveer F. Syeda-Mahmood
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Publication number: 20210011933Abstract: Embodiments provide a computer implemented method of evaluating one or more IR systems, the method including: providing, by a processor, a pre-indexed knowledge-based document to a pre-trained sentence identification model; identifying, by the sentence identification model, a predetermined number of query-worthy sentences from the pre-indexed knowledge-based document, wherein the query-worthy sentences are ranked based on a prediction probability value of each query-worthy sentence; providing, by the sentence identification model, the query-worthy sentences to a pre-trained query generation model; generating, by the query generation model, a query for each query-worthy sentence; and evaluating, by the processor, the one or more IR systems using the generated queries, wherein one or more searches are performed via the one or more IR systems, and the one or more searches are performed in a set of knowledge-based documents including the pre-indexed knowledge-based document.Type: ApplicationFiled: July 10, 2019Publication date: January 14, 2021Inventors: Zhe Liu, Peifeng Yin, Jalal Mahmud, Rama Kalyani T. Akkiraju, Yufan Guo
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Patent number: 10839285Abstract: Local abbreviation expansion is provided through context correlation. In various embodiments, an abbreviation within a phrase is identified. The abbreviation is surrounded by a plurality of words. The words surrounding the abbreviation are provided to a trained neural network. The neural network includes a projection layer adapted to map inputs of the neural network onto a continuous vector space. An expansion is received from the trained neural network. The expansion corresponds to the abbreviation based on the surrounding plurality of words.Type: GrantFiled: April 10, 2017Date of Patent: November 17, 2020Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventor: Yufan Guo